Applying symptom dynamics to accurately predict influenza virus infection: An international multicenter influenza-like illness surveillance study

Jin-Hua Li, Chin-Chieh Wu, Yi-Ju Tseng, Shih-Tsung Han, Andrew Pekosz, Richard Rothman, Kuan-Fu Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background
Public health organizations have recommended various definitions of influenza-like illnesses under the assumption that the symptoms do not change during influenza virus infection. To explore the relationship between symptoms and influenza over time, we analyzed a dataset from an international multicenter prospective emergency department (ED)-based influenza-like illness cohort study.

Methods
We recruited patients in the US and Taiwan between 2015 and 2020 with: (1) flu-like symptoms (fever and cough, headache, or sore throat), (2) absence of any of the respiratory infection symptoms, or (3) positive laboratory test results for influenza from the current ED visit. We evaluated the association between the symptoms and influenza virus infection on different days of illness. The association was evaluated among different subgroups, including different study countries, influenza subtypes, and only patients with influenza.

Results
Among the 2471 recruited patients, 45.7% tested positive for influenza virus. Cough was the most predictive symptom throughout the week (odds ratios [OR]: 7.08–11.15). In general, all symptoms were more predictive during the first 2 days (OR: 1.55–10.28). Upper respiratory symptoms, such as sore throat and productive cough, and general symptoms, such as body ache and fatigue, were more predictive in the first half of the week (OR: 1.51–3.25). Lower respiratory symptoms, such as shortness of breath and wheezing, were more predictive in the second half of the week (OR: 1.52–2.52). Similar trends were observed for most symptoms in the different subgroups.

Conclusions
The time course is an important factor to be considered when evaluating the symptoms of influenza virus infection.
Original languageAmerican English
JournalInfluenza and other Respiratory Viruses
Volume17
Issue number1
DOIs
StatePublished - Jan 2023

Fingerprint

Dive into the research topics of 'Applying symptom dynamics to accurately predict influenza virus infection: An international multicenter influenza-like illness surveillance study'. Together they form a unique fingerprint.

Cite this